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About

Thanassis Souflas is a research engineer specializing in robotic machining, process simulation, and advanced manufacturing automation. His work addresses one of modern manufacturing's most pressing challenges: enabling industrial robots to reliably replace conventional CNC machines in milling and material removal processes. Recognizing that robots' inherent structural compliance and posture-dependent stiffness limit their machining precision, Souflas has developed innovative solutions spanning process planning, dynamic simulation, and real-time monitoring. Among his most influential contributions is his simulation-based approach to robot machining optimization, alongside multi-body dynamic frameworks that model robot-milling interactions with high fidelity — together accumulating over 40 citations. His 2021 method for estimating cutting forces through joint current signals offered a cost-effective, sensor-free monitoring strategy, garnering 15 citations. More recently, his work on in-process chatter detection and digital twin integration reflects a commitment to translating simulation insights into practical, real-time manufacturing intelligence. His research on portable hybrid manufacturing robotic cells further demonstrates a forward-looking vision combining additive and subtractive processes within flexible, deployable platforms. With nearly 75 total citations across six publications, Souflas is establishing himself as a distinctive voice in next-generation robotic manufacturing research.